Accreditation:
EQF7
MaltaSwitzerlandWisconsinCaliforniaWashington
Workload:
2250 hours | 90 ECTS
Tuition cost:
1,75,000 INR

Master of Science in Computer Science

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Kind
Degree
Area
Computer & Mathematical Science
Mode
Fully Online
Language
English
Student education requirement
Undergraduate (Bachelor’s)
Standard length
18 months
Standard delivery length
18 months
Certificates
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\ Overview

The course teaches students comprehensive and specialised subjects in computer science; it teaches students cutting edge engineering skills to solve real-world problems using computational thinking and tools, as well as soft skills in communication, collaboration, and project management that enable students to succeed in real-world business environments. Most of this program is case (or) project-based where students learn by solving real-world problems end to end. This program has core courses that focus on computational thinking and problems solving from first principles. The core courses are followed by specialization courses that teach various aspects of building real-world systems. This is followed by more advanced courses that focus on research level topics, which cover state of the art methods. The program also has a capstone project at the end, wherein students can either work on building end to end solutions to real world problems (or) work on a research topic. The program also focuses on teaching the students the “ability to learn” so that they can be lifelong learners constantly upgrading their skills. Students can choose from a spectrum of courses to specialize in a specific sub-area of Computer Science like Artificial Intelligence and Machine Learning, Cloud Computing, Software Engineering, or Data Science, etc.

Target Audience

-  Ages 19-30, 31-65, 65+
  • Target Group

    • This course is designed for individuals who wish to enhance their knowledge of computer science and its various applications used in different fields of employment. It is designed for those that will have responsibility for planning, organizing, and directing technological operations. In all cases, the target group should be prepared to pursue substantial academic studies. Students must qualify for the course of study by entrance application. A prior computer science degree is not required; however the course does assume technical aptitude; and it targets students with finance, engineering, or STEM training or professional experience.

  • Mode of attendance

    • Online/Blended Learning

  • Structure of the programme - Please note that this structure may be subject to change based on faculty expertise and evolving academic best practices. This flexibility ensures we can provide the most up-to-date and effective learning experience for our students.The Master of Science in Computer Science combines asynchronous components (lecture videos, readings, and assignments) and synchronous meetings attended by students and a teacher during a video call. Asynchronous components support the schedule of students from diverse work-life situations, and synchronous meetings provide accountability and motivation for students. Students have direct access to their teacher and their peers at all times through the use of direct message and group chat; teachers are also able to initiate voice and video calls with students outside the regularly scheduled synchronous sessions. Modules are offered continuously on a publicly advertised schedule consisting of cohort sequences designed to accommodate adult students at different paces. Although there are few formal prerequisites identified throughout the programme, enrollment in courses depends on advisement from Woolf faculty and staff.The degree has 3 tiers: The first tier is required for all students, who must take 15 ECTS. In the second tier, students must select 45 ECTS from elective tiers. Under the guidance of the Academic Staff at Woolf, students may either select exclusively from one specialization track (in which case they will earn that specialization), or they may mix tracks (in which case they will finish without a specialization). Tier Three may be completed in two different ways: a) by completing a 30ECTS Advanced Applied Computer Science capstone project, or b) by completing a 10 ECTS Applied Computer Science project and 20 ECTS of electives from the program.

  • Grading System

    • Scale: 0-100 points

    • Components: 60% of the mark derives from the average of the assignments, and 40% of the mark derives from the cumulative examination

    • Passing requirement: minimum of 60% overall

  • Dates of Next Intake

    • Rolling admission

  • Pass rates

    • 2023 pass rates will be publicised in the next cycle, contingent upon ensuring sufficient student data for anonymization.

  • Identity Malta’s VISA requirement for third country nationals: https://www.identitymalta.com/unit/central-visa-unit/

    • Passing requirement: minimum of 60% overall

  • Dates of Next Intake

    • Rolling admission

  • Pass rates

375 hours | 15 ECTS

Tier 1

125 hours | 5 ECTS

Data Structures

125 hours | 5 ECTS

Introduction to Problem Solving Techniques: Part 1

125 hours | 5 ECTS

Introduction to Computer Programming: Part 1

1125 hours | 45 ECTS

Tier 2

125 hours | 5 ECTS

Design and Analysis of Algorithms

125 hours | 5 ECTS

Advanced Algorithms

125 hours | 5 ECTS

Front End UI/UX Development

125 hours | 5 ECTS

Front End Development

125 hours | 5 ECTS

System Design

125 hours | 5 ECTS

Design Patterns

125 hours | 5 ECTS

Practical Software Engineering

125 hours | 5 ECTS

Foundations of Cloud Computing

125 hours | 5 ECTS

Backend Development

125 hours | 5 ECTS

Data Engineering

125 hours | 5 ECTS

Product Management for Software Engineers

125 hours | 5 ECTS

Distributed Systems with High-Level System Design

125 hours | 5 ECTS

Low-Level Design and Design Patterns

125 hours | 5 ECTS

Advanced Cloud Computing

750 hours | 30 ECTS

Tier 3

750 hours | 30 ECTS

Advanced Applied Computer Science

1125 hours | 45 ECTS

Specialization certificate in Software Engineering

125 hours | 5 ECTS

Design and Analysis of Algorithms

125 hours | 5 ECTS

Advanced Algorithms

125 hours | 5 ECTS

Backend Development

125 hours | 5 ECTS

Front End Development

125 hours | 5 ECTS

Practical Software Engineering

125 hours | 5 ECTS

Data Engineering

125 hours | 5 ECTS

Product Management for Software Engineers

125 hours | 5 ECTS

Low-Level Design and Design Patterns

125 hours | 5 ECTS

Distributed Systems with High-Level System Design

1125 hours | 45 ECTS

Specialization certificate in Cloud Computing

125 hours | 5 ECTS

Foundations of Cloud Computing

125 hours | 5 ECTS

Design and Analysis of Algorithms

125 hours | 5 ECTS

Advanced Algorithms

125 hours | 5 ECTS

Design Patterns

125 hours | 5 ECTS

System Design

125 hours | 5 ECTS

Backend Development

125 hours | 5 ECTS

Front End Development

125 hours | 5 ECTS

Front End UI/UX Development

125 hours | 5 ECTS

Advanced Cloud Computing

\ Intended learning outcomes

Knowledge
Knowledge acquired by the learner at the end of the course:
- Develop a cutting-edge knowledge and understanding of computer science allowing the students to solve real-world engineering and specific computational problems using advanced techniques at the forefront of computer science - Analyze the societal, regulatory, and technological contexts for key computer science applications - Identify real-world problems and apply their understanding of computer science techniques and develop innovative solutions. - Display original thinking on the basis of the knowledge the students gain in the course
Skills
Skills acquired by the learner at the end of the course:
- Develop advanced, innovative, and multi-disciplinary problem-solving skills - Communicate computer science methods and tools clearly and unambiguously to specialised and non-specialised audiences - Develop advanced abilities related to computer science operational procedures and implement them in response to changing environments - Critically evaluate alternative approaches to solving real world engineering and technological problems using cutting edge techniques in computer science on the basis of academic scholarship and case studies, demonstrating reflection on social and ethical responsibilities - Formulate technological judgments and plans despite incomplete information by integrating knowledge and approaches from various computer science domains including machine learning, distributed computing, and cloud computing. - Enquire critically into the theoretical strategies for solving real-world problems using computational thinking and tools. - Develop new skills in response to emerging knowledge and techniques and demonstrate leadership skills and innovation in complex and unpredictable contexts
Competencies
Competencies acquired by the learner at the end of the course:
- Formulate research-based solutions to practical problems in environments of incomplete information. - Manage decisions with autonomy in complex and unpredictable environments. - Organise projects and people in a way that is responsive to changes in the wider technological environment. - Demonstrate learning skills needed to maintain continued, self-directed study.

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